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This role focuses on AI Data Protection transformations, bridging enterprise platforms, cybersecurity, and AI tools. As a hands-on leader, you will drive solutions from discovery to deployment, working closely with clients to architect and implement impactful strategies. You will lead engineering teams and influence deal development. Positioned beyond traditional engineering, this role emphasizes solution architecture at the nexus of platforms and AI technologies, aligning with market trends for embedded technical ownership and end-to-end production deployment.

Lead the comprehensive lifecycle of AI-driven data protection solutions for key clients, translating business, privacy, and security needs into robust technical designs. Act as a front-line technical leader, integrating deeply with client teams to address complex challenges, finalize architectural decisions, and achieve tangible production outcomes.

Design intricate integrations across data protection platforms, AI models, copilots, RAG systems, enterprise data landscapes, and associated security controls. Guide engineering teams through the entire development process, including build, integration, testing, troubleshooting, deployment, and post-launch hardening, ensuring high delivery quality and client trust.

Shape client pursuits by delivering compelling demonstrations, architecting solutions, developing proofs of concept, providing effort estimates, and crafting technical proposals. Develop reusable frameworks, accelerators, reference architectures, and operational guides to enhance the firm’s AI data protection offerings and promote consistent implementation across various sectors and accounts.

Manage client expectations, delivery scope, solution quality, and associated risks. Address technical escalations proactively, while also mentoring teams and fostering long-term client capabilities through thorough documentation and knowledge transfer.

A minimum of 8 to 12 years of experience is required, spanning areas such as data protection, cybersecurity engineering, security architecture, privacy engineering, and cloud security.

Possess a deep understanding of data protection principles, data discovery and classification techniques, Public Key Infrastructure (PKI) and Key Management Service (KMS), and Information Rights Management (IRM).

Demonstrate a strong working knowledge of machine learning (ML), deep learning, natural language processing (NLP), RAG, AI-assisted prioritization, and model risk scoring, with proven experience applying these technologies to solve enterprise-level challenges.

Showcase practical experience in designing and deploying enterprise-scale solutions within cloud and hybrid environments, with a preference for Azure, AWS, or GCP. Experience with cloud-native delivery, APIs, and production systems is consistently expected in comparable roles.

Acquire hands-on expertise with AI/data protection tools, including Microsoft Copilot, GitHub Copilot, Claude Enterprise, Gemini Enterprise, Microsoft Purview, Data Security Posture Management (DSPM) platforms, Python, and other relevant enterprise engineering tools.

Exhibit exceptional client-facing communication skills and the ability to serve as a trusted technical advisor to senior leadership.